AI Can Boost Efficiency of the Renewable Energy Market: IEA Report

With the status of current wind and solar subsidies in the U.S. unclear, the industry needs to brace for impact by making up for the increase in investment risk post-subsidies. How should investors prepare? A post-subsidy world means the renewable energy sector needs to successfully harness and utilize AI and smart data analytics to maximize investment returns.

According to a report by the International Energy Agency, carbon emissions hit a record high in 2018. A new record high is likely in 2019, too. Global energy demand is rising exponentially due to forces like globalization, industrialization and exploding populations. The full impact of these massive forces with renewable energy can't be offset immediately, but with the right advancements and integrations of AI and increased investment in renewable energy, scale can be achieved to meet the challenge, it read.

Renewable energy is how to meet the energy challenges of the 21st century, but there are several factors that are holding the sector back from its full potential. Most notably : the weather. Unpredictable weather can mean that energy captured via solar or wind can fluctuate suddenly, resulting in a less reliable energy stream. But utilizing predictive intelligence can improve the efficacy, productivity, accuracy and reliability of weather forecasts needed to offset the whims of Mother Nature.

Not only can AI improve the reliability of renewable energy streams, it's also creating smart systems that produce quantifiable and qualifiable results to secure the investments needed for a more sustainable future. It's no secret that production and distribution in the energy sector has been advancing at a glacial pace, and unfortunately, the same was becoming true for the renewable subsector, too. But AI, chiefly powered by machine learning, is changing that through the use of real-time assessments on asset performance that can boost efficiency and predictability, the report mentions.

Investors need to see that they're making a sound investment with hard data and actionable conclusions. AI can identify patterns to better understand energy consumption, preparing us for a demand-side economic approach. AI can also recognize when there's an outlier in the data, helping spot and avoid inefficiencies. Additionally, when renewable energy is added to the primary grid, it can be challenging to stabilize the energy flow, but smart systems can help identify and fix distribution issues.